A trust model for sharing ratings of information providers on the Semantic Web

In the context of the Semantic Web, it may be beneficial for a user (consumer) to receive ratings from other users (advisors) regarding the reliability of an information source (provider). We offer a method for building more effective social networks, of trust by critiquing the ratings provided by the advisors. Our approach models the consumer's private reputations of advisors based on ratings for providers whom the consumer has had experience with. It models public reputations of the advisors according to all ratings from these advisors for providers, including those that are unknown to the consumer. Our approach then combines private and public reputations by assigning weights for each of them. Experimental results demonstrate that our approach is robust even when there are large numbers of advisors providing large numbers of unfair ratings. As such, we present a framework for sharing ratings of possibly unreliable sources, of value as users on the Semantic Web attempt to critique the trustworthiness of the information they seek.